Scalable Inference of Overlapping Communities

@inproceedings{Gopalan2012ScalableIO,
  title={Scalable Inference of Overlapping Communities},
  author={Prem Gopalan and David M. Mimno and Sean Gerrish and Michael J. Freedman and David M. Blei},
  booktitle={NIPS},
  year={2012}
}
We develop a scalable algorithm for posterior inference of overlapping communities in large networks. Our algorithm is based on stochastic variational inference in the mixed-membership stochastic blockmodel (MMSB). It naturally interleaves subsampling the network with estimating its community structure. We apply our algorithm on ten large, real-world networks with up to 60,000 nodes. It converges several orders of magnitude faster than the state-of-the-art algorithm for MMSB, finds hundreds of… CONTINUE READING
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